Data Classification, ETL and Python

Harmonize data using AWS Glue and AWS Lake Formation FindMatches ML to build a customer 360 view

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JUNE 26, 2023

Transform raw insurance data into CSV format acceptable to Neptune Bulk Loader , using an AWS Glue extract, transform, and load (ETL) job. When the data is in CSV format, use an Amazon SageMaker Jupyter notebook to run a PySpark script to load the raw data into Neptune and visualize it in a Jupyter notebook.

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Generate training data and cost-effectively train categorical models with Amazon Bedrock

AWS Machine Learning Blog

MARCH 27, 2025

Prerequisites To follow along with this post, set up Amazon SageMaker Studio to run Python in a notebook and interact with Amazon Bedrock. The Python code invokes the Amazon Bedrock Runtime service: import boto3 import json from datetime import datetime import time # Create an Amazon Bedrock Runtime client in the AWS Region of your choice.

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Harmonize data using AWS Glue and AWS Lake Formation FindMatches ML to build a customer 360 view

Generate training data and cost-effectively train categorical models with Amazon Bedrock

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